conduit VS kubernetes

Leverage a service mesh like Istio or Linkerd to manage communication between microservices within the Kubernetes cluster. These service meshes can be configured to intercept JMX traffic and enforce access control policies. Benefits:

Looks like CNCF waved them through Graduation anyway, let's look at policies from July 28, 2021 when they were deemed "Graduated"

All maintainers of the LinkerD project had @boyant.io email addresses. [0] They do list 4 other members of a "Steering Committee", but LinkerD's GOVERNANCE.md gives all of the power to maintainers: [1]

> Ideally, all project decisions are resolved by maintainer consensus. If this is not possible, maintainers may call a vote. The voting process is a simple majority in which each maintainer receives one vote.

And CNCF Graduation policy says a project must "Have committers from at least two organizations" [2]. So it appears that the CNCF accepted the "Steering Committee" as an acceptable 2nd committer, even though the Governance policy still gave the maintainers all of the power.

I would like to know if the Steering Committee voted to remove stable releases from an un-biased position acting in the best interest of the project, or if they were simply ignored or not even advised on the decision.

I'm all for Boyant doing what they need to do to make money and survive as a Company. But at that point my opinion is that they should withdraw the project from the CNCF and stop pretending like the foundation has any influence on the project's governance.

[0] https://github.com/linkerd/linkerd2/blob/489ca1e3189b6a5289d...

From here, we can explore other developments and tutorials on Kubernetes, such as o11y or observability (PLG, ELK, ELF, TICK, Jaeger, Pyroscope), service mesh (Linkerd, Istio, NSM, Consul Connect, Cillium), and progressive delivery (ArgoCD, FluxCD, Spinnaker).

https://linkerd.io/ is a much lighter-weight alternative but you do still get some of the fancy things like mtls without needing any manual configuration. Install it, label your namespaces, and let it do it's thing!

Would it be possible to create a custom extension with the code that authorize traffic based on my custom access token?

Open source API Gateway (Apache APISIX and Traefik), Service Mesh (Istio and Linkerd) solutions are capable of doing traffic splitting and implementing functionalities like Canary Release and Blue-Green deployment. With canary testing, you can make a critical examination of a new release of an API by selecting only a small portion of your user base. We will cover the canary release next section.

I have experimented with other service meshes and I was able to get up to speed quickly: Linkerd = 1 day, Istio = 3 days, NGINX Service Mesh = 5 days, but Consul Connect service mesh took at least 11 days to get off the ground. This is by far the most complex solution available.

https://github.com/linkerd/linkerd2 (random example)

Out of the number of service mesh solutions that exist, the most popular open source ones are: Linkerd, Istio, and Consul. Here at Koyeb, we are using Kuma.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.